





"""simple docstring"""





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE__   =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =  {
    "ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}

class 						lowercase   (   _UpperCAmelCase   ):
      _SCREAMING_SNAKE_CASE							      = 'deta'
      _SCREAMING_SNAKE_CASE							      = {
          'hidden_size': 'd_model',
          'num_attention_heads': 'encoder_attention_heads',
      }





      def __init__(			self ,		lowercase=None ,		lowercase=900 ,		lowercase=2_048 ,		lowercase=6 ,		lowercase=2_048 ,		lowercase=8 ,		lowercase=6 ,		lowercase=1_024 ,		lowercase=8 ,		lowercase=0.0 ,		lowercase=True ,		lowercase="relu" ,		lowercase=256 ,		lowercase=0.1 ,		lowercase=0.0 ,		lowercase=0.0 ,		lowercase=0.02 ,		lowercase=1.0 ,		lowercase=True ,		lowercase=False ,		lowercase="sine" ,		lowercase=5 ,		lowercase=4 ,		lowercase=4 ,		lowercase=True ,		lowercase=300 ,		lowercase=True ,		lowercase=True ,		lowercase=1 ,		lowercase=5 ,		lowercase=2 ,		lowercase=1 ,		lowercase=1 ,		lowercase=5 ,		lowercase=2 ,		lowercase=0.1 ,		lowercase=0.25 ,		**lowercase ,		)						->	Optional[Any]:
            if backbone_config is None:
                  logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""					)
                  lowerCAmelCase    		=			CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]					)
            else:
                  if isinstance(lowercase ,		lowercase					):
                        lowerCAmelCase    		=			backbone_config.pop("""model_type"""					)
                        lowerCAmelCase    		=			CONFIG_MAPPING[backbone_model_type]
                        lowerCAmelCase    		=			config_class.from_dict(lowercase					)

            lowerCAmelCase    		=			backbone_config
            lowerCAmelCase    		=			num_queries
            lowerCAmelCase    		=			max_position_embeddings
            lowerCAmelCase    		=			d_model
            lowerCAmelCase    		=			encoder_ffn_dim
            lowerCAmelCase    		=			encoder_layers
            lowerCAmelCase    		=			encoder_attention_heads
            lowerCAmelCase    		=			decoder_ffn_dim
            lowerCAmelCase    		=			decoder_layers
            lowerCAmelCase    		=			decoder_attention_heads
            lowerCAmelCase    		=			dropout
            lowerCAmelCase    		=			attention_dropout
            lowerCAmelCase    		=			activation_dropout
            lowerCAmelCase    		=			activation_function
            lowerCAmelCase    		=			init_std
            lowerCAmelCase    		=			init_xavier_std
            lowerCAmelCase    		=			encoder_layerdrop
            lowerCAmelCase    		=			auxiliary_loss
            lowerCAmelCase    		=			position_embedding_type
            # deformable attributes
            lowerCAmelCase    		=			num_feature_levels
            lowerCAmelCase    		=			encoder_n_points
            lowerCAmelCase    		=			decoder_n_points
            lowerCAmelCase    		=			two_stage
            lowerCAmelCase    		=			two_stage_num_proposals
            lowerCAmelCase    		=			with_box_refine
            lowerCAmelCase    		=			assign_first_stage
            if two_stage is True and with_box_refine is False:
                  raise ValueError("""If two_stage is True, with_box_refine must be True."""					)
            # Hungarian matcher
            lowerCAmelCase    		=			class_cost
            lowerCAmelCase    		=			bbox_cost
            lowerCAmelCase    		=			giou_cost
            # Loss coefficients
            lowerCAmelCase    		=			mask_loss_coefficient
            lowerCAmelCase    		=			dice_loss_coefficient
            lowerCAmelCase    		=			bbox_loss_coefficient
            lowerCAmelCase    		=			giou_loss_coefficient
            lowerCAmelCase    		=			eos_coefficient
            lowerCAmelCase    		=			focal_alpha
            super().__init__(is_encoder_decoder=lowercase ,		**lowercase					)





      @property
      def        _snake_case     (			self					)						->	int:
            return self.encoder_attention_heads





      @property
      def        _snake_case     (			self					)						->	int:
            return self.d_model





      def        _snake_case     (			self					)						->	Union[str, Any]:
            lowerCAmelCase    		=			copy.deepcopy(self.__dict__					)
            lowerCAmelCase    		=			self.backbone_config.to_dict()
            lowerCAmelCase    		=			self.__class__.model_type
            return output













"""simple docstring"""





import logging
import os

from .state import PartialState

class 						lowercase   (   logging.LoggerAdapter   ):





      @staticmethod
      def        _snake_case     (			lowercase					)						->	Optional[Any]:
            lowerCAmelCase    		=			PartialState()
            return not main_process_only or (main_process_only and state.is_main_process)





      def        _snake_case     (			self ,		lowercase ,		lowercase ,		*lowercase ,		**lowercase					)						->	Dict:
            if PartialState._shared_state == {}:
                  raise RuntimeError(
                      """You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility."""					)
            lowerCAmelCase    		=			kwargs.pop("""main_process_only""" ,		lowercase					)
            lowerCAmelCase    		=			kwargs.pop("""in_order""" ,		lowercase					)

            if self.isEnabledFor(lowercase					):
                  if self._should_log(lowercase					):
                        lowerCAmelCase		,						lowerCAmelCase    		=			self.process(lowercase ,		lowercase					)
                        self.logger.log(lowercase ,		lowercase ,		*lowercase ,		**lowercase					)

                  elif in_order:
                        lowerCAmelCase    		=			PartialState()
                        for i in range(state.num_processes					):
                              if i == state.process_index:
                                    lowerCAmelCase		,						lowerCAmelCase    		=			self.process(lowercase ,		lowercase					)
                                    self.logger.log(lowercase ,		lowercase ,		*lowercase ,		**lowercase					)
                              state.wait_for_everyone()







def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		str				,		SCREAMING_SNAKE_CASE	:		str = None     ):







      '''simple docstring'''




      if log_level is None:
            lowerCAmelCase    		=			os.environ.get("""ACCELERATE_LOG_LEVEL"""				,		SCREAMING_SNAKE_CASE     )
      lowerCAmelCase    		=			logging.getLogger(SCREAMING_SNAKE_CASE     )
      if log_level is not None:
            logger.setLevel(log_level.upper()     )
            logger.root.setLevel(log_level.upper()     )
      return MultiProcessAdapter(SCREAMING_SNAKE_CASE				,		{}     )






